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SCOTTSDALE, Az., February 27, 2020 -- A targeted therapy drug used for breast and kidney cancers may also extend progression-free survival for patients with advanced head and neck cancer who are at high risk for recurrence after standard treatment. Patients enrolled in a randomized phase II trial who received the mTOR inhibitor everolimus were more likely to be cancer-free a year after therapy than those who took a placebo drug, and the benefit persisted for those with mutations in their TP53 gene. The findings may present a new treatment option for a group of patients whose survival rates have not improved in more than 30 years.

The study will be presented at the 2020 Multidisciplinary Head and Neck Cancers Symposium, taking place February 27-29 in Scottsdale, Arizona.

"While cure rates tend to be upwards of 85% for patients with head and neck cancers associated with HPV, they tend to be less than 40% for patients with disease related to smoking," said lead author Cherie-Ann O. Nathan, MD, professor and chair of otolaryngology/head and neck surgery at Louisiana State University (LSU) Health Shreveport and director of head and neck surgery at Feist-Weiller Cancer Center. "These patients are recurring most often, and their survival rates have not changed in decades, despite advances in surgery, radiation therapy and chemotherapy."

To address this disparity, the researchers focused on patients with advanced, HPV-negative head and neck squamous cell carcinoma (HNSCC), or HPV-positive disease and smoking history of more than 10 pack-years, and enrolled 52 patients to receive up to one year of either everolimus or a placebo drug. Eligible patients had to be free of disease after either definitive treatment with chemoradiation therapy or surgery followed by chemoradiation. Researchers then tracked how long they remained cancer-free with additional therapy.

After a year, 81% of patients on everolimus remained progression-free, compared to 57% of those in the placebo group (p=0.039). Dr. Nathan clarified that this timepoint was not stipulated a priori and is a post-hoc analysis. Two-year progression-free survival, which was the primary endpoint, continued to favor everolimus but was no longer significant. Subset analysis determined that for patients with TP53 mutations, the survival difference remained significant for an additional year after they stopped immunotherapy (two-year PFS of 70% vs 22.5%, p=0.036). The difference was not significant at two years for patients without the mutation.

While TP53 mutations occur in almost 80% of HPV-negative, smoking related cases of HNSCC, the potential link between TP53, the mTOR pathway and survival was a surprise to the researchers. "There's really no drug that targets TP53, and so we've never had a targeted therapy for it or considered it an actionable mutation," she said.

Sixteen of the 28 patients on everolimus and seven of the 24 patients on the placebo drug experienced Grade 3 or higher toxicities, including three and five serious adverse events, respectively. Dr. Nathan said the drug's tolerability indicates that it may have potential as longer-term maintenance therapy to delay recurrence for high-risk patients.

"Although the sample size is small, as it closed due to lack of accrual, these finding indicate that patients at high risk for tumor relapse could be given mTOR inhibitors to stall progression and keep any residual cancer cells from growing. Our hope is that head and neck cancer can be treated as chronic disease, similar to some breast cancers," she explained. "Everolimus is used for patients with breast cancer or renal cell cancer for extended periods without major side effects, and there is potential for patients with TP53-mutated head and neck disease to see a survival benefit, as well."

Additional trials are needed to confirm the link between TP53 and survival, as well as to determine the safety of keeping patients with HNSCC on the drug for multiple years.

The number of people infected with the new corona virus continues to skyrocket, with more than 80000 cases worldwide as of the end of February. But there's no vaccine or cure in sight, meaning that doctors can do little more than offer supportive treatment to the very sick and hope their bodies can survive the infection.

Now, however, a coalition of European researchers says that already approved drugs might hold the key to treating the new virus. Their findings have been published as a pre-proof in the International Journal of Infectious Diseases.

"Drug repurposing is a strategy for generating additional value from an existing drug by targeting diseases other than that for which it was originally intended," said Denis Kainov, the senior author on the paper and an associate professor at the Norwegian University of Science and Technology (NTNU). "For example, teicoplanin, oritavancin, dalbavancin and monensin are approved antibiotics that have been shown to inhibit corona- and other viruses in the laboratory."

Kainov and his co-authors say that these and other already tested "safe-in-man" broad-spectrum antiviral drugs are good candidates for treating the disease to start with, given that there are currently no treatments for the new coronavirus illness, which is called COVID-19 by the World Health Organization (WHO).

The WHO says the virus "can cause mild symptoms including a runny nose, sore throat, cough, and fever. It can be more severe for some persons and can lead to pneumonia or breathing difficulties. More rarely, the disease can be fatal. Older people, and people with pre-existing medical conditions (such as, diabetes and heart disease) appear to be more vulnerable to becoming severely ill with the virus."

The advantage of repurposing a drug is that all of the details surrounding the drug development are already known, from the chemical synthesis steps and manufacturing processes to information regarding the different phases of clinical testing.

"Therefore, repositioning of launched or even failed drugs to viral diseases provides unique translational opportunities, including a substantially higher probability of success to market as compared with developing new virus-specific drugs and vaccines, and a significantly reduced cost and timeline to clinical availability," the researchers wrote.

The researchers reviewed information on the discovery and development of broad-spectrum antiviral agents (BSAAs), which are drugs that target viruses from two or more different viral families. They summarized what they found for 120 drugs that had already been shown to be safe for humans use and created a database, which is freely accessible. Thirty-one of these were found by the researchers to be possible candidates for prophylaxis and treatment of the COVID-19 infections. The researchers also found that clinical investigations have recently begun of five possible drug candidates to treat the virus that causes COVID-19.

"In the future, BSAAs will have global impact by decreasing morbidity and mortality from viral and other diseases, maximizing the number of healthy life years, improving the quality of life of infected patients and decreasing the costs of patient care," the researchers concluded.

Weather is an ever-present force in consumers' daily lives, yet there is little marketing research on how it affects consumers and businesses. A new UBC Sauder School of Business study reveals that sunny and snowy conditions trigger consumers to mentally visualize using products associated with the respective weather, which leads to consumers placing a higher value on them. Researchers also found the link between weather and higher product valuation only works for products that are related to being outside.

For example, if the product is a beach towel, and the sun is out - a customer is not just looking at the beach towel, they are likely imagining themselves lying on the beach towel in the sun, increasing the value of the product in the customer's mind.

"We think the mental simulation only works in sunshine and snow because these weather conditions have a positive association with outside activities," said JoAndrea Hoegg, study co-author and UBC Sauder associate professor. "There are not many activities that are enabled by rain. Most products associated with the rain, such as rain coats and umbrellas, are just to protect oneself against the rain and not to enable activities."

For the study, the researchers analyzed sales data over a one-year period from a large online auction site and the coinciding weather conditions of when and where those purchases took place. The researchers also analyzed the number of images displayed to consumers for each product to measure the degree of mental simulation ¬- the more images that were shown, the easier it was for customers to mentally simulate themselves using the products.

The researchers also conducted online surveys where participants were asked about the weather outside, and then were shown products that were either for indoor or outdoor use to determine how the participants value the products.

Hoegg suggests that companies that sell a wide range of products online can benefit most from the insights that this research provides. Online sellers often use algorithms to determine what products to feature and how those products are priced. These algorithms will take different seasons into account, but not the daily weather in the locations where their customers are. Incorporating the constantly updated data from a weather-tracking website into an online seller's algorithms would allow them to take advantage of the effects of mental simulation and increased product valuation.

It's also important for companies to note that if a product is poorly designed or unattractive, the positive weather effect will backfire, because if a customer imagines an activity using a poor-quality product, they're less likely to purchase it.

Scientists have shown that some key points of animal evolution -- like the ones leading to humans or insects -- were associated with a large loss of genes in the genome. The study, published in Nature Ecology & Evolution, compared over 100 genomes to investigate what happened at the gene level during the evolution of animals after their origin.

During evolution, organisms can gain new genes to perform new functions, lose other genes that are not used anymore, and recycle old ones into new functions. Previous studies have shown that the acquisition of new genes played a major role in the origin of the animal kingdom, and it is assumed that most organisms become more complex by acquiring new genes.

Dr Jordi Paps from the University of Bristol together with PhD student, Cristina Guijarro-Clarke at the University of Essex, and Professor Peter Holland from the University of Oxford, discovered that gene loss has actually been more important during the evolution of the animal kingdom than previously thought.

Animals can be split into major evolutionary lineages. One is deuterostomes: comprising humans and other vertebrates as well as sea stars or sea urchins. Another is ecdysozoans: encompassing the largest group of animals, the arthropods (insects, lobsters, spiders, millipedes), as well as other moulting animals like roundworms. These two lineages include some of the animals considered to be more complex.

However, the research team's analyses has shown that the respective last common ancestors of deuterostomes and ecdysozoans suffered unprecedented levels of gene losses, and that the increase in complexity or diversity of species is not always coupled with a rise in the number of new genes.

Dr Jordi Paps, lead author and Lecturer from Bristol's School of Biological Sciences, explained: "A larger implication is that the evolution of the animal kingdom is not driven by an increase in the number of genes, and in evolution does not invariably mean becoming more complex.

"We are planning to use the same type of approach to study how the genomes of parasitic animals, such as taenia or roundworms, lose and gain genes to see if we can find therapeutic targets to fight the diseases caused by these parasites."

The next step for the research would be to see if this pattern is also seen in other major lineages in the tree of life, other than animals.

Like most other species, male sea turtles will mate with any female sea turtle they can. However, when it comes to female sea turtles and mate selection, it's a little more complex. Sea turtles are known to have multiple mates, yet there is no consensus on why they do.

It is believed that female sea turtles may mate multiply to ensure fertilization, which will result in multiple paternity within their nests, providing "fertilization insurance," so to speak. However, researchers from Florida Atlantic University suggest that this fertilization insurance hypothesis might not be so compelling after all.

Findings from their study, published in the journal Ecology and Evolution, provide insights into the relative numbers of males present in the breeding population - such measures are hard to obtain because males never come ashore. Furthermore, because conservation efforts are often focused on protected nests and nesting beaches (ensuring protection of the genetic output of nesting females), this study helps to provide a rough measure of how many males' genes are effectively receiving protection as well.

For the study, researchers examined paternity patterns in a sample of nesting loggerhead (Caretta caretta) female sea turtles on Sanibel Island in southwestern Florida. Sea turtles lay several nests over the course of a nesting season. Sanibel Island is monitored by the Sanibel Captiva Conservation Foundation (SCCF) who determined that during the 2016 nesting season, 634 loggerhead nests were laid on the island. Over that nesting season, sea turtles that laid more than one nest at that beach and a subset of their hatchlings were assessed to find out how many fathers were represented in the clutches (the eggs in each nest). Researchers compared genotypes to examine 36 of their clutches to determine paternity patterns between subsequent clutches.

Multiple mating can occur when the benefits of mating outweigh the costs, but if costs and benefits are equal, no pattern is expected. The researchers hypothesized that, if the benefits of mating outweigh the costs, females should mate multiply both early and throughout the breeding season.

Surprisingly, what researchers discovered is that most of these Sanibel Island female sea turtles were monogamous - 75 percent of the females they analyzed had mated singly. No male was represented in more than one female's clutches.

"Female sea turtles have the remarkable ability to store sperm. The simplest explanation of these singly-fathered Sanibel Island nests is that the females successfully mated once and stored sufficient sperm to fertilize all the eggs in the multiple clutches we observed," said Jacob A. Lasala, Ph.D., senior author and a graduate of biological sciences who trained under Jeanette Wyneken, Ph.D., co-author and a professor of biological sciences, and Colin Hughes, Ph.D., co-author and an associate professor of biological sciences in FAU's Charles E. Schmidt College of Science. "Females likely mate at the beginning of the season and use stored sperm for multiple clutches."

In this population, males appear to complete their breeding season before all females complete nesting and depart for foraging grounds. Given the dispersion of loggerhead turtles and the lack of evidence of pair bonds, the researchers say that it is improbable that females who laid singly sired nests would seek out the same specific males to replenish their sperm storage between clutches.

"If females were mating with multiple males to increase opportunities for and benefits from males with some advantageous heritable traits, we would expect to see higher emergence success and/or larger and presumably, more robust hatchlings in multiple paternity clutches," said Wyneken. "There were no differences between primary versus secondary clutches or between single versus multiple paternity clutches."

The frequency of multiple paternity was 22 percent (eight of 36 nests), which is lower than previously reported for this nesting beach (67 percent, 34 of 51 nests). The researchers did not find any consistent pattern across the subsequent multiple paternity clutches, suggesting benefits to loggerhead females probably equals their costs. All clutches had male genotypes that persisted from the first clutch to subsequent clutches (including one of 50 days past the first observed clutch).

The four female loggerhead turtles in the study with new fathers in subsequent clutches were smaller and possibly younger than those that mated with one male. The researchers think it's possible that smaller females or those breeding for the first time may be unable to reject persistent or aggressive males and hence their nests would be prone to multiple paternity.

"If there is little benefit and little cost to multiple mating by females, it's reasonable to hypothesize that larger and more experienced females may be more effective in controlling their numbers of mates than smaller, neophyte nesters," said Lasala, who is currently a postdoctoral research fellow at Mote Marine Laboratory. "While loggerhead females may mate between nesting events, that behavior appears to be relatively rare."

Many children with autism face developmental delays, including communication and behavioral challenges and difficulties with social interaction. This makes learning new skills a major challenge, especially in traditional school environments.

Previous research suggests socially assistive robots can help children with autism learn. But these therapeutic interventions work best if the robot can accurately interpret the child's behavior and react appropriately.

Now, researchers at USC's Department of Computer Science have developed personalized learning robots for children with autism. They also studied whether the robots could estimate a child's interest in a task using machine learning.

In one of the largest studies of its kind, the researchers placed a socially assistive robot in the homes of 17 children with autism for one month. The robots personalized their instruction and feedback to each child's unique learning patterns during the interventions.

After the study was completed, the researchers also analyzed the participants' engagement and determined the robot could have autonomously detected whether or not the child was engaged with 90% accuracy. The results of the experiments were published in the "Frontiers in Robotics and AI" and "Science Robotics," journals on Nov. 6 and Feb. 26, respectively.

Making robots smarter

Robots are limited in their ability to autonomously recognize and respond to behavioral cues, especially in atypical users and real-world environments. This study is the first to model the learning patterns and engagement of children with autism in a long-term, in-home setting.

"Current robotic systems are very rigid," said lead author Shomik Jain, a progressive degree mathematics student advised by socially assistive robotics pioneer Professor Maja Matari?.

"If you think of a real learning environment, the teacher is going to learn things about the child, and the child will learn things from them. It's a bidirectional process and that doesn't happen with current robotic systems. This study aims to make robots smarter by understanding the child's behavior and responding to it in real- time."

The researchers stress the goal is to augment human therapy, not replace it.

"Human therapists are crucial, but they may not always be available or affordable for families," said Kartik Mahajan, an undergraduate student in computer science and study co-author. "That's where socially assistive robots like this come in."

Enhancing the learning experience

Funded by a National Science Foundation (NSF) grant given to Matari?, the research team placed Kiwi the robot in the homes of 17 children with autism spectrum disorders for about a month. The child participants were all aged between 3 and 7 and from the greater Los Angeles area.

During almost daily interventions, the children played space-themed math games on a tablet while Kiwi, a 2-foot tall robot dressed like a green feathered bird, provided instruction and feedback.

Kiwi's feedback and the games' difficulty were personalized in real-time according to each child's unique learning patterns. Matari?'s team in the USC Interaction Lab accomplished this using reinforcement learning, a rapidly growing subfield of artificial intelligence (AI).

The algorithms monitored the child's performance on the math games. For instance, if a child answered correctly, Kiwi would say something like, "Good job!". If they got a question wrong, Kiwi might give them some helpful tips to solve the problem, and adjust the difficulty and feedback in future games. The goal was to maximize difficulty, while also not pushing the learner to make too many mistakes.

"If you have no idea what the child's ability level is, you just throw a bunch of varying problems at them and it's not good for their engagement or learning," said Jain.

"But if the robot is able to find an appropriate level of difficulty for the problems, then that can really enhance the learning experience."

The ultimate frontier

There's a popular saying among people with autism and their families: If you have met one person with autism, you have met one person with autism.

"Autism is the ultimate frontier for robotic personalization, because as anyone who knows about autism will tell you, every individual has a constellation of symptoms and different severities of each symptom," said Matari?, Chan Soon-Shiong Distinguished Professor of Computer Science, Neuroscience, and Pediatrics and Interim Vice President of Research.

This presents a particular challenge for machine learning, which usually relies on spotting consistent patterns in huge amounts of similar data. That's why personalization is so important.

"If we take a cue from a child, we can achieve so much more than just following a script," said Matari?. "Normal AI approaches fail with autism. AI methods require a lot of similar data and that just isn't possible with autism, where heterogeneity reigns."

The researchers tackled this problem in their analysis of the children's engagement after the intervention. Computer models of engagement were developed by combining many types of data, including eye gaze and head pose, audio pitch and frequency, and performance on the task.

Making these algorithms work using real-world data presented a major challenge, given the accompanying noise and unpredictability.

"This experiment was right in the center of their learning experience," said Kartik, who helped install the robots in the children's homes.

"There were cats jumping on the robot, a blender going off in the kitchen, and people coming in and out of the room." As such, the machine learning algorithms had to be sophisticated enough to focus on pertinent information related to the therapy session and dismiss environmental "noise."

Improving human-robot interaction

Assessments were conducted before and after the month-long interventions. While the researchers expected to see some improvements in participants, the results surpassed their expectations. At the end of the month's intervention, 100% of the participants demonstrated improved math skills, while 92% also improved in social skills.

In post-experiment analyses, the researchers were also able to glean some other interesting information from the data that could give us a peek into the recipe for ideal child-robot interactions.

The study observed higher engagement for all participants shortly after the robot had spoken. Specifically, participants were engaged about 70% of the time when the robot had spoken in the previous minute, but less than 50% of the time when the robot had not spoken for more than a minute.

While a personalized model for every user is ideal, the researchers also determined it was possible to achieve adequate results using engagement models trained on data from other users.

Moreover, the study observed caregivers only had to intervene when a child lost interest for a longer period of time. In contrast, participants usually re-engaged by themselves after shorter periods of disinterest. This suggests robotic systems should focus on counteracting longer periods of disengagement.

Matari?'s lab will continue to study the data gathered from the experiment: One active sub-project involves analyzing and modeling the children's cognitive-affective states, including emotions such as confusion or excitement. The project, led by progressive degree in computer science student Zhonghao Shi, aims to design affect-aware socially assistive robot tutors that are even more sensitive to the emotions and moods of its users in the context of learning.

"The hope is that future studies in this lab and elsewhere can take all the things that we've learned and hopefully design more engaging and personalized human-robot interactions," said Jain.

The impacts of the corona virus on people's health and daily life, stock markets, and businesses illustrate the increasingly interconnected nature of the challenges facing governments around the world. Putting systemic thinking at the centre of policymaking will be essential to address these issues in an era of rapid and disruptive change, according to a new joint report by IIASA and the Organisation for Economic Co-operation and Development (OECD).

Systemic thinking for policymaking: The potential of systems analysis for addressing global policy challenges in the 21st century, aims to highlight to policymakers how systems research can be used to understand the complex issues facing society, anticipate the consequences of our decisions, and build resilience. The authors argue that, to tackle planetary emergencies linked to the environment, the economy, and sociopolitical systems, policymakers need to understand their systemic properties, including tipping points, interconnectedness, and resilience.

"The systems approach can promote cross-sectoral, multidisciplinary collaboration in the process of policy formulation by taking proper account of the crucial linkages between issues generally treated separately within different specialisations and scientific and institutional "silos"," said Gabriela Ramos, OECD Chief of Staff. "The approach provides a methodology to achieve a better understanding of the non-linear behaviour of complex systems and improve the assessment of the consequences of policy interventions. The ultimate objective is to improve the capacity of policies to deliver better outcomes for people."

"Unless we adopt a systems approach, unless we employ systems thinking, we will fail to understand the world we are living in. This is a world made up of complex systems, systems of systems interacting with each other, and changing each other by that interaction and the links between them. If we are to tackle these issues, governments must change the ways in which they make and implement policies. An acceptance of complexity shifts governments from a top-down siloed culture to an enabling culture where evidence, experimentation, and modeling help to inform and develop stakeholder engagement and buy-in," adds IIASA Director General Albert van Jaarsveld.

"The report shows the considerable potential of mainstreaming systemic thinking into policymaking, including within the OECD itself. As part of an agreed work program between the two organizations, the aim is to establish specific bilateral projects in the different areas of policymaking," says Acting Chief Operations Officer of IIASA, Jan Marco Müller.

The report highlights the application of systems thinking beyond the fields of analysis, modeling, and the formulation of policy, and that systems thinking has immediate application in developing human capital through education, training, and team building. Perspectives are drawn from a range of disciplines and methodologies including economics, social science, and policymaking, but also from the physical and biological sciences and engineering. The authors show how cross-sectoral, multidisciplinary collaboration can take account of the crucial linkages between issues generally treated within different specializations, and scientific and institutional silos.

Closer trade cooperation in combination with robust land use strategies could, for instance, increase the resilience of global food markets to the impacts of climate change, while an integrated approach to the management of water, energy, and land would provide experts and policymakers with a better understanding of the benefits and challenges of sustainably meeting future demand for resources. Another example cited in the report is the link between education and demographic change, where the authors highlight how lifelong education strategies, starting from early childhood, can promote productive working lives and healthy ageing.

Scientists from the University of Surrey have identified mutations in a gene in an Escherichia coli (E. coli) model that could help explain a form of anti-microbial resistance (AMR) known as 'persistence'.

Publishing their findings in the eminent journal PNAS scientists identified these mutations in the gene ydcI, which cause increased numbers of bacterial cells known as persisters. Persisters are a tiny fraction of cells that are present in all bacterial infections. They are known to survive antibiotic treatment and can cause recurrent infections. Their presence in the population means that treatment for some diseases, such as tuberculosis (TB), has to be continued for up to six months, which is expensive and impractical in many countries. Despite their biological importance, very little is known about these persisters.

Using single cell computerised tracking on an E. coli model, researchers found that memory loss -- whereby the bacteria have an increased tendency to 'forget' how to grow normally -- could help to explain persisters' formation. Lacking the memory of their sibling cells, persisters tend to be smaller and slower growing than other cells in the populations.

Scientists found that mutations in the gene ydcI caused more of these forgetful cells and thereby more persisters. These persisters have also been shown to be a hotspot of further development of genetic AMR.

The identification of these gene mutations in ydcl and the ground breaking insight on persister cells could lead to the development of novel therapeutic strategies that target these cells and prevent them becoming resistant to antibiotics.

Johnjoe McFadden, Professor of Molecular Genetics at the University of Surrey, said: "Antimicrobial resistance is a growing threat to global public health, and without effective antibiotics the success of medical treatments will be compromised.

"There is an urgent need within the science community to learn as much as we can about AMR and develop techniques to tackle it. Our findings on persister cells and the identification of the mutations in the gene ydcI in E. coli bacteria are a huge step forward in the fight against AMR and give us a greater understanding of how persister cells operate."

Dr Suzie Hingley-Wilson, Lecturer in Bacteriology at the University of Surrey, said: "What we have found is that persister cells have experienced "memory loss" and forget to grow as they should. This 'forgetfulness' means that they become small, slow and difficult to treat with antibiotics. Persisters are often responsible for reoccurrence of bacterial disease following antibiotic treatment and are a reservoir of further AMR development.

"The more we know about what makes these clinically relevant persisters different, the higher our chances of developing new techniques to tackle AMR."

For many years, researchers have disagreed as to why some global areas have an extremely large species richness, while others have almost no species. In other words, what explains the uneven distribution of biodiversity on earth?

Some researchers have claimed that the species richness of a region primarily reflects the number of new species that evolve there, and that species disperse more or less randomly out from these areas. Others have argued that high levels of ambient energy - such as high temperatures and ample rainfall that stimulate plant growth - set an upper limit to how many species may coexist locally. But now, it appears that an entirely third explanation probably plays the most important role.

In a new study, researchers from the University of Copenhagen and the Smithsonian Institution have investigated the geographic distributions of all species from three different classes of vertebrates in South America: birds, mammals and amphibians. The results are published in the scientific journal Nature Communications.

'Biologists have discussed this problem for more than a hundred years and have put forward all sorts of likely explanations - but we have yet to find the final answer. With this study, we can say that species richness is not just a mechanical consequence of a contemporary climate with high ambient energy in the form of solar radiation and plant growth. Our research shows that the cause underlying species richness to a large extent should be found in evolution. Animal species have their evolutionary niches that control how they disperse', says Michael K. Borregaard, Associate Professor at the Center for Macroecology, Evolution and Climate at the GLOBE Institute.

Species' Patterns Follow Natural Habitats

Michael K. Borregaard of the Center for Macroecology, Evolution and Climate (CMEC) at GLOBE Institute has led the new study. In collaboration with Professor Carsten Rahbek, Director of CMEC, and Gary R. Graves of the National Museum of Natural History at the Smithsonian Institution, they developed new models to calculate and explain species richness in South America.

Their models are based on amphibians, birds and mammals. They tally the species of the given animal class within grid squares of 110 by 110 kilometres, and investigate how many of these are present in surrounding areas. In this way, the researchers can describe how the composition of species communities change across the continent, thus getting an indication as to how they might have dispersed.

'When we look at the distribution of species, we see a clear pattern. And this same pattern emerges regardless of whether we look at birds, amphibians or mammals, which are entirely distinct groups. The pattern of shared species composition very closely follows the boundaries of South America's various natural habitats or vegetation biomes. This confirms our hypothesis that species richness is explained by how animals' natural niches limit how they disperse across the continent over evolutionary time. In this way, historical evolutionary adaptations to various types of vegetation will play a key role for biodiversity', explains Michael K. Borregaard.

The World's Largest Hotspot for Biodiversity

The researchers have divided the entire South American continent into grid squares of 110 x 110 kilometres and recorded the presence of all animal species in the three classes: 2869 bird species, 1146 mammal species and 2265 amphibian species.

'We have chosen South America because it is the world's largest hotspot for biodiversity. And the contrasts between the vegetation biomes are huge. There are pretty distinct boundaries between the Amazon, the Cerrado savannah and the Andes mountains because they are clearly seperate natural vegetation types', adds Michael K. Borregaard.

He explains that studies such as the present are essential if the international community is to solve the global biodiversity crisis.

'Right now, we have a worldwide crisis, where we are losing species at an elevated rate. If we are to solve that crisis, we need to know what causes biodiversity. Without that knowledge, it will be difficult to protect the richness of species', he concludes.

Older people's risk of recurrent fractures decreases by 18 percent if the care they receive is more structured and preventive, through fracture liaison services. This is shown by a study from the University of Gothenburg, Sweden.

Sweden and the Nordic region in general rank high in international statistics on osteoporotic (fragility) fractures among the over-50s. After the age of 50, the life-time risk of sustaining a fragility fracture is 50% among women and 25% among men. Sweden's care services in this area are estimated to cost billions of euros annually, and the human suffering is immense.

Following fragility fractures, the usual outcomes are functional impairment and higher morbidity and mortality rates. For up to two years after the first fracture the risk of having another is four to five times, and thereafter twice, as high as in people of the same age who have had no fractures.

Fracture prevention is therefore vital, and at a few hospitals fracture liaison services have been introduced. Examples are Skaraborg Hospital and Sahlgrenska University Hospital, which are both included in the present study from Sahlgrenska Academy at the University of Gothenburg.

The method involves identification, risk evaluation, examination, and treatment of patients straight after the first fracture. To keep track of the process there are "fracture coordinators," usually working at the specialist clinics that attend to fracture patients or treat osteoporosis, the underlying disease.

The study, published in the Journal of Bone and Mineral Research, is based on data about 21,083 patients from a total of four hospitals in Västra Götaland County in 2012-2017. All patients aged 50 and over with classic osteoporotic (fragility) fractures of the hip, vertebra, upper arm, wrist or pelvis were included.

The researchers' primary aim was to investigate the proportion of patients who suffered a new fragility fracture after the first. All the patients with a fracture after the introduction of the local fracture liaison service were compared with historical controls.

"It's very pleasing that fewer patients were affected by new fractures and thereby spared the suffering a fracture involves. Fewer fractures also means savings for the society," says Kristian Axelsson, the first author of the article, a University of Gothenburg PhD student, and resident physician specializing in orthopedics at Skaraborg Regional Hospital in Skövde. Axelsson is in charge of the fracture liaison service in Skaraborg.

While the risk of a recurrent fracture was 18 percent lower after the introduction of fracture liaison service, the risk of fall injuries was unchanged. According to the researchers, this suggests that the risk reduction can be linked to the increase in prescription of drugs against osteoporosis. Among the oldest old, over 82 years of age, only 16 fracture patients needed to be screened in order to prevent a new fracture in 5 years.

Neither was there any increase in the use of medication, or reduced risk of a new fracture, at those hospitals where no organizational changes were made during the study period. The analyses were adjusted for differences between the groups compared, which did not change the results.

Mattias Lorentzon is the senior author of the study and a professor of geriatrics at the University of Gothenburg, and chief physician at Sahlgrenska University Hospital in charge of the Hospital's fracture liaison service.

"The results show that simple changes in our care routines have the intended effect, with fewer fractures as a result. It's now particularly important for the extremely few hospitals that have fracture liaison services to become more numerous, to reduce inequality in care, for the good of the patients," he says.

How did the universe begin? How does quantum mechanics, the study of the smallest things relate to gravity and the study of big things? These are some of the questions physicists have been working to solve ever since Einstein released his theory of relativity.

Formulas show that baby universes pops in and out of the main universe. However, we don't realize or experience this as humans. To calculate how this scales, theoretical physicists devised the so-called JT gravity, which turns the universe into a toy-like model with only one dimension of time or space. These restricted parameters allows for a model in which scientists can test their theories.

Building on the work of others, Professor Kazumi Okuyama of Shinshu University and Kazuhiro Sakai of Meiji Gakuin University set out to show how JT gravity, KdV equation and the macroscopic loop are related, thus pointing to the fact that gravity and quantum mechanics are unified. In the process, the duo succeeded in calculating the birth of baby universes 46 times which has never been done before, due to the fact the more times this is calculated the more things get increasingly complicated. Previously, Peter Zograf was able to calculate this 20 times.

The mathematical KdV equation formulated in the late 19th Century has been thought to be linked to gravity since the 1990s. The KdV equation was first used to show how water waves behave, for example inside the canals in waterway laden Holland, solitons can be observed, or how a crest of a water wave continues unchanged for a long time when not disturbed. The macroscopic loop was also said to be related to the gravity in the 1990s.

Waves and gravity are thought to be comparable in how they manifest themselves. The holographic principle was introduced by Gerard 't Hooft as a way to understand how gravity and quantum mechanics work. When these theories are combined, one can think of the 3D physical as the gravity and the information that it is sprung from; flat like how a hologram is on a credit card. This speaks to the dimensions in space. There is no formula yet for the holographic principle.

The bulk-boundary correspondence idea is similar to this in that the bulk is the three dimensional manifestation of the boundary which is the information that gives rise to the hologram.

Professor Okuyama was able to show in this study that the JT gravity, KdV equation and macroscopic loop are intimately connected, pointing to the fact that quantum mechanics and gravity are indeed unified holographically in this model. He hopes to keep working to solve this problem in physics by devising a method to calculate the birth of baby universes not just in the "toy model" but for the existent universe.

Now researchers are presenting guidelines for how active matter, such as cells and microorganisms, can best be studied using machine learning techniques. The guidelines can help others navigate the new field, which can significantly improve research in active matter.

Machine learning has proven to be very useful for the study of active matter, a collective term referring to things like cells and microorganisms. The field is quite new and growing fast. In an attempt to inspire more researchers to try the methods a group of scientists have published a paper in prestigious publication Nature Machine Intelligence reviewing what has been accomplished so far - and what lies ahead.

"We give an outline of how the field should evolve in the future, both opportunities and challenges. There are always challenges associated with AI and machine learning. Essentially, we've created a set of guidelines that could save people some time, and possible prevent them from doing things wrong in their process," says Giovanni Volpe, senior lecturer at the Department of Physics, University of Gothenburg.

These guidelines to utilizing machine learning on active matter presented are fairly hands-on. For starters, the researchers suggest that all data used should be pre-processed, and that one should be very careful when applying a machine learning model outside the range on which it was trained.

"Finally, it's important to use physics-informed models. That could mean, for example, that you should try to make your model conserve energy," says Giovanni Volpe.

When it comes to the benefits of using machine learning to study active matter, the group has identified a number of advantages. One is that when working with active matter you can acquire very good quality data at large quantities, which you can use to train the machine learning model and understand how the model works. Another advantage is that you can follow the dynamics of a system over many lengths- and time scales.

"You can follow a particle for time scales from micro-seconds up to days. This means you can connect microscopic dynamics to large-scale outcomes. We think this can be useful for creating models that can infer long- term properties from something very small, or vice versa. You can't do this in other systems, like economical systems," says Giovanni Volpe.

Please Note: The 2020 American Physical Society (APS) March Meeting that was to be held in Denver, Colorado from March 2 through March 6 has been canceled. The decision was made late Saturday (February 29), out of an abundance of caution and based on the latest scientific data available regarding the transmission of the coronavirus disease (COVID-19). See our official release on the cancelation for more details.

DENVER, COLO., FEBRUARY 28, 2020 -- A new influenza strain appears each flu season, rendering past vaccines ineffective. Antibiotic resistant 'superbugs' quickly develop genetic resistance to existing drugs. Rapidly changing viruses and bacteria complicate vaccine and drug research. Scientists at the 2020 American Physical Society March Meeting in Denver will share their work on the emergence and evolution of modern pathogens.

Predicting Resistance

Antibiotic resistance is an increasingly serious threat to modern medicine. Resistance generally arises from evolutionary processes, when bacteria change their genetic make-up by mutation or uptake of resistance genes from other bacteria and become less susceptible to drugs. While high doses of antibiotics can clearly select for resistant bacteria, it remains unclear by which mechanisms and rates low doses can cause bacteria to become resistant. A team of researchers from the University of Cologne and University of Uppsala has now developed a new quantitative model to predict how Escherichia coli evolve mutational resistance to different levels of the antibiotic streptomycin.

"We show that growth rates of a class of resistance mutants can be predicted from the way mutations affect cell metabolism", said Fernanda Pinheiro, a physicist at the University of Cologne and shared first author of the study together with Omar Warsi, a microbiologist at Uppsala University.

Concepts and methods for predictive analysis established in this work might inform the least-resistance prone treatment protocols, drug targets, and new antibiotic candidates, finding potential applications in medicine, drug development and public health.

Toward a Universal Flu Vaccine

The influenza virus mutates so quickly that it requires a new vaccine against it every year.

However, Assaf Amitai and his colleagues, Maya Sangesland, Daniel Lingwood, and Arup
Chakraborty, report on the mechanisms that may allow the immune system to respond to a
broad distribution of flu strains. The approach that they have explored uses nanoparticles with specific geometries and compositions.

"We are not trying to just increase overall protection against the flu, but also to make the
immune system do something it does not naturally do," said Amitai, a theoretical biophysicist at
the Massachusetts Institute of Technology.

Immune cells typically attack the head of hemagglutinin, the flu surface protein. Hemagglutinin's head mutates very frequently, while its stem does not. The researchers have studied how the use of multiple sequentially administered nanoparticle-based vaccines with specific geometries and compositions may be able to train the immune system to respond to hemagglutinin's stem instead of its head. The results provide a mechanistic understanding of the underlying immunological processes.

Streamlining Drug Discovery

Certain species of harmful bacteria, like Clostridium difficile, have already evolved resistance to most existing therapeutics, and the lengthy process of creating new drugs makes it difficult to develop timely specialized treatments. But Anushree Chatterjee and her team have created a new platform and approach for combating antibiotic resistance. The new method can accelerate the development of therapeutics, according to Chatterjee, a bioengineer at the University of Colorado, Boulder.

The researchers developed a new, interdisciplinary technique, called the Facile-Accelerated Specific Therapeutic (FAST) platform, that can produce tailored therapeutic molecules for each pathogen. Combining bioinformatics, synthetic biology and chemistry, and nanotechnology, the platform can develop medical therapies within a week from discovery to testing in the lab.

Antibiotics and the Gut

Gut bacteria perform many helpful functions, but still feel the impact of antibiotics--no matter the dose.

"Even weak doses of antibiotics can have a surprisingly strong impact on the microbiome," said Raghuveer Parthasarathy, a physicist at the University of Oregon. He and his colleagues analyzed how sublethal doses of antibiotics changed the behavior of gut bacteria in zebrafish.

The team found that weak doses alter the shape of lone bacteria and the growth of bacterial clusters in such a way that they struggle to remain in the gut. Taking sublethal doses of antibiotics can lead to the gut purging antibiotic-exposed bacteria, sending them out into the environment.

Please Note: The 2020 American Physical Society (APS) March Meeting that was to be held in Denver, Colorado from March 2 through March 6 has been canceled. The decision was made late Saturday (February 29), out of an abundance of caution and based on the latest scientific data available regarding the transmission of the coronavirus disease (COVID-19). See our official release on the cancelation for more details.

DENVER, COLO., FEBRUARY 28, 2020 -- Climate change is one of the most daunting challenges facing the planet and humanity, so scientists around the globe are working to provide more clarity about the scale of the problem and searching for solutions.

At the 2020 American Physical Society March Meeting in Denver, researchers will share their climate work, including: decoding the climate system's behavior, a new approach to climate modeling, a novel material that can morph from cornstarch to industrial plastic and then back into an edible again, using satellite imaging to promote high-yield organic farming, and making the case for innovation via nuclear sources to create cheaper carbon-free energy.

Decoding the Climate System's Dynamic, Complex Behavior

The climate system is dynamic, with complex behavior that includes oscillatory modes that are more or less regular, such as the El Niño-Southern Oscillation (ENSO), as well as highly irregular, noisy phenomena like the weather systems of mid-latitudes. How does changing atmospheric composition affect this complex behavior? What about changes in the amplitude and frequency of extreme events like hurricanes, floods, or droughts?

Michael Ghil, physicist and distinguished research professor at the University of California, Los Angeles, will present a new framework for studying the behavior of the climate system's complex dynamics when subjected to anthropogenic effects, and how these effects may modify its key features.

"These key features include stationary states that don't change at all in time, pure oscillations whose periodic behavior changes in relatively simple ways, and more complicated entities like the 'butterfly' of the Lorenz convection model," said Ghil. The changes that arise from the interaction between the climate's internal variability and the forcing are visually fascinating and scientifically quite striking.

This work "provides the means for a better understanding of the ways climate has changed within the last two centuries, since the industrial revolution, as well as for more robust predictions of future behavior, as human-induced changes accelerate," he said.

Combining Physical Climate Models and Superfast Algorithms

Tapio Schneider, climate scientist and professor of environmental science and engineering at California Institute of Technology, will present a new approach to climate change modeling that fuses extensive use of data with physical, biological, and chemical models and can potentially achieve a leap forward in the accuracy of climate predictions.

"It will allow us to quantify uncertainties in predictions, which are important for planning," says Schneider. "For example, cities planning their stormwater management infrastructure to withstand the next 100 years' worth of floods need answers about the likely range of climate outcomes for cost-effective adaptation strategies."

This approach intertwines process-informed models of the climate system, and especially of small-scale features such as clouds or ocean turbulence that cannot be resolved within a global computational model, with algorithms developed for calibration and uncertainty quantification in computationally expensive computer models that are up to 1,000 times faster than existing algorithms.

A Fully Recyclable, Closed-Loop Composite Resin?

John Dorgan, professor of chemical engineering and materials science at Michigan State University, will present a fully recyclable composite resin. The material is designed for use within a closed loop: it starts out as cornstarch, morphs into durable plastics, and can then be reclaimed as an edible, food-grade potassium lactate.

"The liquid material contains a biodegradable plastic known as PLA (polylactide), which is derived from biomass and creates fewer greenhouse gases than other polyesters," says Dorgan. "As a liquid it can be used to impregnate fibers to make composite materials like carbon fiber automotive panels or large fiberglass wind turbine blades, or even the ubiquitous cultured stone countertops found in kitchens."

Once these materials reach the end of their service life, they can be dissolved in fresh liquid and the solids easily separated. "We cast carbon fiber panels and verified their terrific mechanical properties, then digested them to recover potassium lactate so we could make gummy bear candies, which I ate," Dorgan says.

Wanted: Cheaper, Carbon-Free Energy Sources

Ross Koningstein, general engineer and director emeritus for Google, will describe what it will take to find a solution to climate change and why he views advanced fission, fusion, and other nuclear sources as areas that are ripe for innovation.

"We need to put a spotlight on inspiring smart people to work on the hard problems--and ensure that their research and development is well funded and organized for success," he says.

Please Note: The 2020 American Physical Society (APS) March Meeting that was to be held in Denver, Colorado from March 2 through March 6 has been canceled. The decision was made late Saturday (February 29), out of an abundance of caution and based on the latest scientific data available regarding the transmission of the coronavirus disease (COVID-19). See our official release on the cancelation for more details.

DENVER, COLO., FEBRUARY 28, 2020 -- Using physics to study different types of animal motion, such as burrowing worms or flying flocks, can reveal how animals behave in different settings. By using principles and technology from fields like fluid mechanics, scientists can track and measure animals in motion. At the 2020 American Physical Society March Meeting in Denver, researchers will present the various ways they quantify animal movement--and subsequently, better understand the animal world.

Social Behaviors in Flocks

Flocks seem to move as one unified organism, with each bird knowing its place and anticipating the group's future movements. Although indistinguishable to the human eye, birds actually modify their flying behaviors based on the type of flock they are flying in.

"You can take the same bird with the same social structure in the same part of the world, and put them into two different contexts. They behave collectively in both cases, but the way they do so is not at all the same," said Nicholas Ouellette, an environmental engineer at Stanford University.

He and his colleagues captured videos of jackdaws, a common species related to crows, flying in two types of flocks: transit flocks were when the birds all flew home to nest at night, while mobbing flocks were when the birds swarmed a predator.

The results indicate jackdaws in transit model their flight pattern after a set number of their neighbors--no matter how close or far those neighbors might be. However, mobbing jackdaws orient themselves by maintaining a set metric distance from surrounding birds. The birds' interactions change based on flock type, suggesting the motives for some types of collective behavior influence animal behavior on an individual level.

Multiple Animals, One Neural Network

It can be difficult to identify and quantify animal behavior in the wild. A neural network developed by Talmo Pereira and his colleagues helps scientists track multiple animals in social settings and monitor their movement.

"The reason why we like to think of behavior in terms of motion is because most of what the brain does is control the body so that it can interact with the world," said Pereira, part of a team in the Center for the Physics of Biological Function and the Neuroscience Institute at Princeton University. The imaging technique uses principles similar to those behind motion capture suits in Hollywood. But unlike actors, animals don't have to wear specialized harnesses. Recently, the team modified their previous tracking method so it can distinguish each animal in a group even during close interactions.

Having a richer representation of animals' movement adds to the quantitative understanding of behavior, according to Pereira.

A Photoelastic Stress Test for Worm Behavior

Deriving quantitative data from behavior requires flexible problem solving. Kelly Dorgan has been studying how marine worms burrow through muddy sediment and the forces they exert.

To replicate sea sediment's physical properties, Dorgan, an ecologist at the Dauphin Island Sea Lab, turned to an unusual substitute. Jell-O has a similar fracture behavior, as sediment. This means that forces exerted by worms burrowing in muds can be directly calculated from forces measured in Jell-O

"Because I could measure forces, I came up with the first realistic measure of the energetic cost of burrowing," said Dorgan. The results showed that despite the strength they use to burrow, worms actually expend very little energy in terms of increased metabolic rate because they move so slowly.